Category Ranking
98%
Total Visits
921
Avg Visit Duration
2 minutes
Citations
20
Article Abstract
In this article, a novel online adaptive control scheme is developed for the optimal control issues of integrated electric-gas systems with partially unknown dynamics, by combining the decentralized event-triggered mechanism and adaptive dynamic programming techniques. Initially, the complex electric-gas coupling network is modeled in the state-space form. By virtue of neural networks (NNs), the NN-based identifier and the critic NN are designed to approximate the unknown drift dynamic and the optimal value function in an online fashion, respectively. Subsequently, the decentralized event-triggered control strategies are devised under the identifier-critic framework. Moreover, a novel decentralized event-triggered scheme with the dead-zone operation is proposed, which updates the controller and actuator signals only when the triggering condition is violated. As such, the computation complexity and the waste of communication resources can be significantly reduced. On the foundation of the Lyapunov theory, the uniform ultimate boundedness stability of the closed-loop control system and the exclusion of the Zeno behavior are proven. Finally, the effectiveness of the developed algorithm is verified through two numerical examples.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1109/TCYB.2025.3597930 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
In this article, a novel online adaptive control scheme is developed for the optimal control issues of integrated electric-gas systems with partially unknown dynamics, by combining the decentralized event-triggered mechanism and adaptive dynamic programming techniques. Initially, the complex electric-gas coupling network is modeled in the state-space form. By virtue of neural networks (NNs), the NN-based identifier and the critic NN are designed to approximate the unknown drift dynamic and the optimal value function in an online fashion, respectively.
View Article and Find Full Text PDFEvent-triggered optimal control for modular reconfigurable manipulators with input constraints based on model predictive control.
ISA Trans
August 2025
Ltd.of China Power Engineering Consulting Group, Northeast Electric Power Design Institute Co, 130012, Changchun, China. Electronic address:
This paper proposes an event-triggered optimal control method for modular reconfigurable manipulators(MRMs) based on model predictive control(MPC). By using a decentralized optimization method based on MPC, the optimal control problem of MRMs is transformed into independent optimization tasks for each module, while a global MPC optimization framework is utilized to coordinate the modules, ultimately optimizing the overall performance of the entire system. In order to avoid the safety hazards caused by excessive torque, hyperbolic tangent function is added to constrain the input torque.
View Article and Find Full Text PDFNeural network-based adaptive decentralized safe control for interconnected nonlinear systems with time delays.
ISA Trans
July 2025
School of Information Science and Engineering, Northeastern University, Shenyang, 110819, Liaoning, PR China.
This paper addresses the safety control issue for interconnected nonlinear systems with time delays and asymmetric input constraints by proposing a decentralized dynamic event-triggered (DET) controller based on the adaptive dynamic programming (ADP) method. Unlike other studies on large-scale interconnected systems, the equilibrium point of the system under our study is not zero. Firstly, by incorporating a discount factor and introducing a barrier function and a Lyapunov-Krasovskii (L-K) function, we construct a cost function for the interconnected system with a non-zero equilibrium point, time delay, and constraints, thereby transforming the constrained decentralized control problem into an unconstrained optimal control problem (OCP).
View Article and Find Full Text PDFDecentralized Adaptive Secure Control of Nonlinear NCSs Under Hybrid Attacks via Event-Triggering.
IEEE Trans Cybern
August 2025
This article is concerned with the event-based secure tracking control issue for a class of nonlinear networked control systems (NCSs) under malicious sensor and actuator attacks. In the sensing channel, a modified event-triggered (ET) control scheme based on a continuous function is developed to resist sparse sensor attacks, which can evade the control design difficulties associated with discontinuous information transmission. Then, a high-order filter with a secure data preselector is presented to obtain reliable state estimation from a group of output measurements.
View Article and Find Full Text PDFIn this article, a double-channel event-triggered control method is developed for nonlinear uncertain interconnected systems using backstepping techniques, which introduces event-triggering mechanisms at both the sensor and controller sides. Using event-triggering mechanism at the sensor side presents a challenge to the backstepping control design as the discontinuous state/output signals received at the controller side result in nondifferentiable virtual control signals. This challenge becomes more pronounced when considering more general types of event-triggering mechanisms.
View Article and Find Full Text PDF